Javed Khan

USPTO Granted Patents = 11 (Patent Applications = 1)

CIPO Patents = 1

EPO Patents = 3 (Patent Applications = 3)

Average Co-Inventor Count = 4.0

ph-index = 2

Forward Citations = 104(Granted Patents)

Company Filing History:

11 out of 3,435

National Institutes of Health, a Component of the US Dept. of Health & Human Services

patents

1 out of 1,926

University System of Maryland

patents

where one patent can have more than one assignee

Years Active: 2010-2025

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11 patents (USPTO):Sort by Forward Citations

Abstract keywords

1. 12453780 - Monoclonal antibodies specific for fibroblast growth factor receptor 4 (FGFR4) and methods of their use (2025-10-28),

2. 11078286 - Monoclonal antibodies specific for fibroblast growth factor receptor 4 (FGFR4) and methods of their use (2021-08-03),

3. 8620592 - Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states (2013-12-31),

4. 8283122 - Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma (2012-10-09),

5. 8263759 - Sets of probes and primers for the diagnosis of select cancers (2012-09-11),

6. 8216783 - Over-expression and mutation of a tyrosine kinase receptor FGFR4 in tumors (2012-07-10),

7. 8065092 - Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states (2011-11-22),

8. 8017938 - Apparatus for microarray binding sensors having biological probe materials using carbon nanotube transistors (2011-09-13),

9. 7783431 - Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states (2010-08-24),

10. 7774143 - Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states (2010-08-10),

11. 7655397 - Selections of genes and methods of using the same for diagnosis and for targeting the therapy of select cancers (2010-02-02),

Title: Javed Khan: Innovator in Cancer Treatment

Introduction

Javed Khan is a prominent inventor based in Derwood, MD, who has made significant contributions to the field of cancer treatment through his innovative research and development of monoclonal antibodies. With a total of 11 patents to his name, Khan's work focuses on targeting specific cancer receptors to improve diagnosis and treatment options for various types of cancer.

Latest Patents

Khan's latest patents include the development of monoclonal antibodies specific for fibroblast growth factor receptor 4 (FGFR4) and methods of their use. These antibodies are selected from immunized mice, immunized rabbits, and a human scFv library, specifically binding to FGFR4. His patents also describe chimeric antigen receptors, antibody-drug conjugates, immunoconjugates, bispecific antibodies, and immunoliposomes that incorporate FGFR4-specific antibodies. The compositions developed can be utilized to diagnose or treat FGFR4-positive cancers, including rhabdomyosarcoma, lung cancer, liver cancer, breast cancer, pancreatic cancer, and prostate cancer.

Career Highlights

Throughout his career, Javed Khan has worked with esteemed organizations such as the National Institutes of Health, a component of the US Department of Health & Human Services, and the University System of Maryland. His work in these institutions has allowed him to advance his research and contribute to the scientific community significantly.

Collaborations

Khan has collaborated with notable colleagues, including Carsten Peterson and Paul S. Meltzer, enhancing the impact of his research through teamwork and shared expertise.

Conclusion

Javed Khan's innovative work in developing targeted therapies for cancer exemplifies the importance of research in improving patient outcomes. His contributions to the field through his patents and collaborations continue to pave the way for advancements in cancer treatment.

This text is generated by artificial intelligence and may not be accurate.